A Simple Algorithm for Oncidium Orchid Cut Flower Grading with Deep Learning

Abstract

Utilizing emerging information technology in agriculture automation is arisen for reducing human errors and increasing the productivity and quality. This paper proposes a simple algorithm OCG with deep learning network to determine the grading levels of Oncidium orchid cut flowers which are related to the sale prices. The algorithm consists of two phases. The grading criteria about lengths are estimated by image analysis in the first phase, while the grading criteria about counting branches are predicted using deep learning in the second phase. The experimental results show that our algorithm can achieve accuracy of 0.8 and the algorithm is practical.